A special local clustering algorithm for identifying the genes associated with alzheimers disease

IEEE Transactions on Nanobioscience

Volumn 9, Issue 1, 2010, Pages 44-50

  Pang, Chao Yang ^a,b   Hu, Wei ^b   Hu, Ben Qiong ^c   Shi, Ying ^a   Vanderburg, Charles R ^d   Rogers, Jack T ^e   Huang, Xudong ^a  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

^b SICHUAN NORMAL UNIVERSITY   (China)

^c CHENGDU UNIVERSITY OF TECHNOLOGY   (China)

^d The Harvard Center for Neurodegeneration & Repair   (United States)

^e MASSACHUSETTS GENERAL HOSPITAL   (United States)

Author keywords

Algorithm; Alzheimer's disease (AD); Compact class; Local clustering (LC) feature; Special local clustering (SLC)

Indexed keywords

ALZHEIMER'S DISEASE; EXPRESSION PATTERNS; GENE IDENTIFICATION; GENE MICROARRAYS; IN-CONTROL; LOCAL CLUSTERING; LOCAL CLUSTERING (LC) FEATURE; NOVEL CLUSTERING;

GENE EXPRESSION; POWDERS;

CLUSTERING ALGORITHMS;

ALGORITHM; ALZHEIMER DISEASE; ARTICLE; BIOLOGY; CLUSTER ANALYSIS; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETIC PREDISPOSITION; GENETICS; HUMAN; METABOLISM; METHODOLOGY;

ALGORITHMS; ALZHEIMER DISEASE; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; GENE EXPRESSION PROFILING; GENETIC PREDISPOSITION TO DISEASE; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS;

EID: 77950527729     PISSN: 15361241     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNB.2009.2037745     Document Type: Article

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